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Recent developments in the shipping industry have opened some unprecedented trade opportunities on various levels. Be it individual consumption or business needs, the thought of receiving a package on the same day or within 4-hour from some other business or industry in the urban area is worth appreciating. The congestion on ground transportation modes is higher than ever. Since currently the same-day delivery in urban areas is carried mainly by ground modes, the catchment area of this delivery service is limited. The On-Demand Mobility for cargo can elevate the concept of express shipping in revolutionary ways. It will not only increase the catchment area thereby encompassing more business and consumers but will also expedite the delivery as these vehicles will fly over the ground traffic. The objective of this study was to estimate the total demand for ODM Cargo operations and study its effect on ODM passenger operations. The area of interest for this study was Northern California (17 counties). Annual cargo flows in the study area were rigorously analyzed through databases like Transearch, Freight Analysis Framework-4, and T-100 International for freight. The results of this study are presented through a parametric analysis of market share. The end product also includes the flight trajectories (with flight plan) of daily ODM cargo flights in the study region. The On-Demand Mobility cargo operations are expected to complement passenger On-Demand Mobility operations. Therefore, the effect of ODM cargo operations on the passenger ODM operations was also analyzed in this study. The major challenge faced in this study was the unavailability of datasets with the desired level of details and refinements. Since the movement of cargo is mostly done by private companies, the detailed records of shipments are often not public knowledge. / Master of Science / The recent advancements in shipping industry has made transfer of goods both domestic and international, swifter and more reliable. Nowadays, some business and consumers in urban areas have the options of few-hours or same day delivery. Currently the same-day delivery in urban areas is carried mainly by ground modes (trucks) and hence the catchment area of this delivery service is limited. Adding to it, the traffic congestion on the urban roads is a major hinderance in growth of such services. The On-Demand Mobility for cargo can reform express shipping in revolutionary ways. The concept vehicle can fly over the ground traffic. Therefore, it will increase the catchment area thereby encompassing more business and consumers, along with faster delivery options in currently serviced areas. For the study, we analyzed different databases for annual cargo flows in the region. Seventeen counties in the Northern California were chosen as the study area (or region). The study was focused on estimating the potential market (demand) for the On-Demand Mobility Cargo operations. Multiple set of results were calculated for different market shares that On-Demand Mobility can potentially capture in cargo operations. Flight trajectories (with flight plan) for daily ODM cargo flights were the final product. The On-Demand Mobility cargo operations are expected to complement passenger ODM operations. Therefore, the effect of ODM cargo operations on the passenger ODM operations was also analyzed in this study. The major challenge faced in this study was the unavailability of datasets with the desired level of details and refinements.

We report on two studies that involve molecular dynamics (MD) simulations of grain boundary motion in nanocrystalline (nc) nickel. The first study is conducted to examine the effects of an applied tensile stress on the grain boundary motion in 5 nm3 nc-Ni specimens, half of which contain free surfaces, while the other half have periodic boundary conditions. Grain boundary sliding (GBS) and grain rotation are the deformation mechanisms exhibited by the nc-Ni specimens, in contrast to dislocation-mediated deformation mechanisms found in bulk samples. Specimens that contain free surfaces display a lower yield stress and a lower average grain boundary velocity compared to their periodic counterparts. These phenomena are attributed to the higher degree of grain boundary sliding present within the free surface specimens. The second study examines thermal effects of various annealing temperatures on grain boundary motion in 5 nm3 periodic nc-Ni specimens. It is found that grain growth exhibits a linear relationship with time, as opposed to parabolic grain growth observed in bulk metals. During the annealing process, it is also observed that the average grain boundary energy decreases with t-1/2, as grains oriented themselves in a lower-energy configuration with their neighbors via grain rotation. An Arrhenius plot of average grain boundary velocity and energy per atom within a grain boundary displays identical slopes, and thus, identical activation energies of ~ 53 kJ for both characteristics. This can be attributed to the fact that grain boundary velocity and energy per atom are governed by the same entity, which is grain boundary diffusion. The annealed samples display a grain rotation-coalescence growth mechanism, where adjacent grains rotate concurrently, to decrease the misorientation energy of the grain boundary between them. It is observed that some grains have achieved the same orientation at the end of the growth process, indicating that the grain boundary has been annihilated, and the two grains have coalesced into a single larger grain. / Master of Science

The Coronavirus pandemic changed the normal lives across the country as strategies for mitigating the spread of the virus were put in place. Daily life was moved to a virtual setting as much as possible and typical mobility purposes changed or were eliminated. Shared transportation ridership declined dramatically in response to the pandemic, with reported drops of up to 90% across the United States. Mobility providers were tasked with determining strategies to encourage ridership during the risky time. The main research question that was explored in this study was, "What is the impact of the Coronavirus pandemic on public transit and micromobility ridership?" The study aimed to determine important factors that potential riders considered and emphasized in their decision making. The research approach was to use a custom-developed stated preference survey. The survey collected opinions about public transit and micromobility ridership during and emerging from the Coronavirus pandemic. The study focused on Blacksburg, VA as it has both public transit and micromobility services. Personal characteristics and stated important factors that influenced potential rider decisions were determined to understand what is most important to potential riders. Mobility providers can use these findings to better address rider concerns and make informed decisions on provided service. Therefore, encouraging an increase in shared transportation ridership. / Master of Science / The Coronavirus pandemic changed the normal lives across the country as strategies for mitigating the spread of the virus were put in place. Daily life was moved to a virtual setting as much as possible and typical mobility purposes changed or were eliminated. Shared transportation ridership declined dramatically in response to the pandemic, with reported drops of up to 90% across the United States. Mobility providers were tasked with determining strategies to encourage ridership during the risky time. The main research question that was explored in this study was, "What is the impact of the Coronavirus pandemic on public transit and micromobility ridership?" The study aimed to determine important factors that potential riders considered and emphasized in their decision making. The research approach was to use a custom developed stated preference survey. The survey collected opinions about public transit and micromobility ridership during and emerging from the Coronavirus pandemic. The study focused on Blacksburg, VA as it has both public transit and micromobility services. Factors that influenced potential rider decisions were determined. Mobility providers can use these factors to better address rider concerns and make informed decisions on provided service.

By advancing technologies in both hardware and software, it is possible to support more complex applications. Wireless Sensor Networks (WSNs) comprised of tiny sensing devices with wireless radios are the key enablers for future Internet of Things(IoT) applications, where collecting measurements and delivering them to their destination is the most important task. In traditional sensor networks, sensor nodes were typically stationary and each node periodically measured and sent data to the next predefined router. However, in current applications, some nodes are expected to move. For instance, in health monitoring applications, where patients with sensors attached to their body are free to move in the hospital or their houses. Software Defined Networking (SDN) is a technique that was conventionally used in wired networks, and recently was used in some wireless networks, such as cellular and wireless local area networks. The idea of SDN is to provide more flexibility in the network by getting the advantage of re-programmability of the network devices during run-time. In networks based on SDN, the control plane is shifted from the infrastructure to a higher level in order to provide re-configuration. The controller decides on updating forwarding rules by getting some feedback from nodes in the network. In wireless sensor networks, the feedback may contain information related to the link quality and available resources such as battery level and the location of the sensor node (number of hops away from the sink). In this thesis, a study ofseveral relevant SDN-based architectures for wireless sensor networks is given, outlining the main advantages and disadvantages for each. In addition, some mobility solutions in sensor networks such as localization, routing and hand-off algorithms are explored. One of the drawbacks with SDN is that it was originally built for wired networks there experience with mobility does not exist. Thus the thesis considers the possibility to use SDN solutions in WSN were certain applications are in need of mobility. Finally, the thesis propose mobility solution for sensor networks that takes advantage of SDN and uses a handoff algorithm. In fact, the hand-off mechanism is achieved by means of control message exchanges that is supervised by the controller.

Nowadays with the rapid development of cities, understanding the human mobility patterns of subscribers is crucial for urban planning and for network infrastructure deployment. Today mobile phones are electronic devices used for analyzing the mobility patterns of the subscribers in the network, because humans in their daily activities they carry mobile phones for communication purpose. For effective utilization of network infrastructure (NI) there is a need to study on mobility patterns of subscribers.   The aim of the thesis is to simulate the geospatial Telenor mobility data (i.e. three different subscriber categorized segments) and provide a visual support in google maps using google maps API, which helps in decision making to the telecommunication operators for effective utilization of network infrastructure (NI).    In this thesis there are two major objectives. Firstly, categorize the given geospatial telenor mobility data using subscriber mobility algorithm. Secondly, providing a visual support for the obtained categorized geospatial telenor mobility data in google maps using a geovisualization simulation tool.    The algorithm used to categorize the given geospatial telenor mobility data is subscriber mobility algorithm. Where this subscriber mobility algorithm categorizes the subscribers into three different segments (i.e. infrastructure stressing, medium, friendly). For validation and confirmation purpose of subscriber mobility algorithm a tetris optimization model is used. To give visual support for each categorized segments a simulation tool is developed and it displays the visualization results in google maps using Google Maps API.   The result of this thesis are presented to the above formulated objectives. By using subscriber mobility algorithm and tetris optimization model to a geospatial data set of 33,045 subscribers only 1400 subscribers are found as infrastructure stressing subscribers. To look informative, a small region (i.e. boras region) is taken to visualize the subscribers from each of the categorized segments (i.e. infrastructure stressing, medium, friendly).    The conclusion of the thesis is that the functionality thus developed contributes to knowledge discovery from geospatial data and provides visual support for decision making to telecommunication operators. Nowadays with the rapid development of cities, understanding the human mobility patterns of subscribers is crucial for urban planning and for network infrastructure deployment. Today mobile phones are electronic devices used for analyzing the mobility patterns of the subscribers in the network, because humans in their daily activities they carry mobile phones for communication purpose. For effective utilization of network infrastructure (NI) there is a need to study on mobility patterns of subscribers.   The aim of the thesis is to simulate the geospatial Telenor mobility data (i.e. three different subscriber categorized segments) and provide a visual support in google maps using google maps API, which helps in decision making to the telecommunication operators for effective utilization of network infrastructure (NI).    In this thesis there are two major objectives. Firstly, categorize the given geospatial telenor mobility data using subscriber mobility algorithm. Secondly, providing a visual support for the obtained categorized geospatial telenor mobility data in google maps using a geovisualization simulation tool.    The algorithm used to categorize the given geospatial telenor mobility data is subscriber mobility algorithm. Where this subscriber mobility algorithm categorizes the subscribers into three different segments (i.e. infrastructure stressing, medium, friendly). For validation and confirmation purpose of subscriber mobility algorithm a tetris optimization model is used. To give visual support for each categorized segments a simulation tool is developed and it displays the visualization results in google maps using Google Maps API.   The result of this thesis are presented to the above formulated objectives. By using subscriber mobility algorithm and tetris optimization model to a geospatial data set of 33,045 subscribers only 1400 subscribers are found as infrastructure stressing subscribers. To look informative, a small region (i.e. boras region) is taken to visualize the subscribers from each of the categorized segments (i.e. infrastructure stressing, medium, friendly).    The conclusion of the thesis is that the functionality thus developed contributes to knowledge discovery from geospatial data and provides visual support for decision making to telecommunication operators.